issue_comments: 279846111

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https://github.com/pydata/xarray/issues/1262#issuecomment-279846111 https://api.github.com/repos/pydata/xarray/issues/1262 279846111 MDEyOklzc3VlQ29tbWVudDI3OTg0NjExMQ== 1217238 2017-02-14T21:46:09Z 2017-02-14T21:46:09Z MEMBER

CC @pydata/xarray in case anyone else has opinions here

Benefits in favor would be that I suspect XArray already has mechanisms for coercion and such and it would reduce the number of total libraries.

We really don't have much existing machinery. Two things we have that might be useful:

  • a couple of mixin classes for easily defining custom array types. This could be a nice building block, but it's self-contained and only a few dozen lines of code.
  • some existing code for function dispatch to either numpy or dask.array. This is quite messy, somewhat xarray-specific and not worth copying.

Fewer libraries is definitely nice, but I see this as more of a secondary rather than primary goal.

More broadly, doing this project right will need strong separation of concerns from xarray's handling of labeled arrays. So there's not a huge amount to be gained by doing it in the same repository.

Argument against is that XArray is currently only focused on indexed and labeled arrays, and possible it doesn't want to deal with the dtype mess.

I would love to see this project be successful and integrated with xarray. But better dtypes is tangental to our current focus, and project maintenance is already stretched pretty thin -- there's still a lot of core functionality to build out for manipulation of labeled arrays.

So I'm not comfortable with building this in xarray at this time. But I would be happy to revisit this decision when you have a design document, prototype and someone committed to developing and maintaining the module.

 
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